这可能只是.NET框架分配的内存对象没有正确页面对齐的问题,但我不明白为什么零拷贝对我来说比非零拷贝慢。
我将在这个问题中包含内联代码,但可以在此处查看完整的源代码:https ://github.com/kwende/ClooMatrixMultiply/blob/master/GiantMatrixOnGPU/GPUMatrixMultiplier.cs 。
由于这是我第一次尝试让零拷贝工作,我写了一个简单的矩阵乘法示例。我首先初始化我的 OpenCL 对象:
private void Initialize()
{
// get the intel integrated GPU
_integratedIntelGPUPlatform = ComputePlatform.Platforms.Where(n => n.Name.Contains("Intel")).First();
// create the compute context.
_context = new ComputeContext(
ComputeDeviceTypes.Gpu, // use the gpu
new ComputeContextPropertyList(_integratedIntelGPUPlatform), // use the intel openCL platform
null,
IntPtr.Zero);
// the command queue is the, well, queue of commands sent to the "device" (GPU)
_commandQueue = new ComputeCommandQueue(
_context, // the compute context
_context.Devices[0], // first device matching the context specifications
ComputeCommandQueueFlags.None); // no special flags
string kernelSource = null;
using (StreamReader sr = new StreamReader("kernel.cl"))
{
kernelSource = sr.ReadToEnd();
}
// create the "program"
_program = new ComputeProgram(_context, new string[] { kernelSource });
// compile.
_program.Build(null, null, null, IntPtr.Zero);
_kernel = _program.CreateKernel("ComputeMatrix");
}
...如果我的代码尚未初始化,这只会执行一次。然后我进入主体。对于非零副本,我执行以下操作:
public float[] MultiplyMatrices(float[] matrix1, float[] matrix2,
int matrix1Height, int matrix1WidthMatrix2Height, int matrix2Width)
{
if (!_initialized)
{
Initialize();
_initialized = true;
}
ComputeBuffer<float> matrix1Buffer = new ComputeBuffer<float>(_context,
ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer,
matrix1);
_kernel.SetMemoryArgument(0, matrix1Buffer);
ComputeBuffer<float> matrix2Buffer = new ComputeBuffer<float>(_context,
ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer,
matrix2);
_kernel.SetMemoryArgument(1, matrix2Buffer);
float[] ret = new float[matrix1Height * matrix2Width];
ComputeBuffer<float> retBuffer = new ComputeBuffer<float>(_context,
ComputeMemoryFlags.ReadWrite | ComputeMemoryFlags.CopyHostPointer,
ret);
_kernel.SetMemoryArgument(2, retBuffer);
_kernel.SetValueArgument<int>(3, matrix1WidthMatrix2Height);
_kernel.SetValueArgument<int>(4, matrix2Width);
_commandQueue.Execute(_kernel,
new long[] { 0 },
new long[] { matrix2Width, matrix1Height },
null, null);
unsafe
{
fixed (float* retPtr = ret)
{
_commandQueue.Read(retBuffer,
false, 0,
ret.Length,
new IntPtr(retPtr),
null);
_commandQueue.Finish();
}
}
matrix1Buffer.Dispose();
matrix2Buffer.Dispose();
retBuffer.Dispose();
return ret;
}
您可以看到我如何为我的所有 ComputeBuffer 分配显式设置 CopyHostPointer。这执行得很好。
然后我对(包括设置“UseHostPointer”和调用 Map/Unmap 而不是 Read)进行以下调整:
public float[] MultiplyMatricesZeroCopy(float[] matrix1, float[] matrix2,
int matrix1Height, int matrix1WidthMatrix2Height, int matrix2Width)
{
if (!_initialized)
{
Initialize();
_initialized = true;
}
ComputeBuffer<float> matrix1Buffer = new ComputeBuffer<float>(_context,
ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer,
matrix1);
_kernel.SetMemoryArgument(0, matrix1Buffer);
ComputeBuffer<float> matrix2Buffer = new ComputeBuffer<float>(_context,
ComputeMemoryFlags.ReadOnly | ComputeMemoryFlags.CopyHostPointer,
matrix2);
_kernel.SetMemoryArgument(1, matrix2Buffer);
float[] ret = new float[matrix1Height * matrix2Width];
ComputeBuffer<float> retBuffer = new ComputeBuffer<float>(_context,
ComputeMemoryFlags.ReadWrite | ComputeMemoryFlags.UseHostPointer,
ret);
_kernel.SetMemoryArgument(2, retBuffer);
_kernel.SetValueArgument<int>(3, matrix1WidthMatrix2Height);
_kernel.SetValueArgument<int>(4, matrix2Width);
_commandQueue.Execute(_kernel,
new long[] { 0 },
new long[] { matrix2Width, matrix1Height },
null, null);
IntPtr retPtr = _commandQueue.Map(
retBuffer,
false,
ComputeMemoryMappingFlags.Read,
0,
ret.Length, null);
_commandQueue.Unmap(retBuffer, ref retPtr, null);
_commandQueue.Finish();
matrix1Buffer.Dispose();
matrix2Buffer.Dispose();
retBuffer.Dispose();
return ret;
}
然而,时机说明了一切。我的程序吐出这个:
CPU矩阵乘法:1178.5ms
GPU矩阵乘法(复制):115.1ms
GPU矩阵乘法(零拷贝):174.1ms
GPU(带副本)快 10.23892 倍。
GPU(零拷贝)快 6.769098 倍。
...所以零拷贝速度较慢。